Yes, Infoscribe can manage several essential geospatial preprocessing tasks, including orthorectification, georeferencing, alignment, and reprojection of images or maps, depending on project requirements and client-provided formats. The goal is to deliver fully usable data for GIS environments, mapping applications, or geospatial AI pipelines.

Orthorectification: Infoscribe can correct distortions caused by camera angles, terrain relief, or sensors to produce geometrically accurate images. This enables the creation of orthophotos or orthomosaics suitable for precise ground measurements.

Georeferencing: The team can integrate or adjust the spatial coordinates of an image using control points, sensor metadata, or client-provided reference systems. This ensures that the data aligns correctly within a standard coordinate system.

Alignment: Infoscribe can align multiple images or datasets (satellite, drone, LiDAR, maps) so that they overlay perfectly, which is essential for temporal monitoring, change detection, or multimodal data fusion.

Reprojection: Data can be reprojected into the desired coordinate system (WGS84, Lambert, UTM, etc.) to ensure compatibility with GIS tools, geospatial models, or deep learning platforms.

These processes can be performed prior to annotation work or delivered as standalone services. Infoscribe adapts the complexity of the processing according to technical requirements, expected precision, and the nature of the geospatial project.

Infoscribe supports a wide range of geospatial formats to ensure maximum compatibility with GIS tools, mapping platforms, geospatial analysis pipelines, and deep learning systems applied to spatial data. This versatility allows seamless integration of data from satellites, drones, LiDAR sensors, or traditional cartographic sources.

Supported Raster Formats (Satellite or Drone Imagery)

Infoscribe accepts and delivers the following formats:

• GeoTIFF / georeferenced TIF
• Standard TIFF
• JPEG2000
• PNG / JPEG (for simplified or derived exports)

These formats retain the spatial metadata required for GIS applications.

Supported Vector Formats

For annotation or the creation of feature layers:

• Shapefile (.shp)
• GeoJSON
• KML / KMZ
• GPKG (GeoPackage)

These formats allow delivery of annotations as polygons, lines, or points.

Point Clouds / 3D Data

Infoscribe accepts and delivers:

• LAS / LAZ
• PLY
• XYZ

These formats are used for LiDAR projects, 3D modeling, or volumetric analysis.

Supported Coordinate Systems

Infoscribe can work with:

• WGS84 (EPSG:4326) — the most common for GPS and satellite data
• UTM (all zones) — suitable for precise ground measurements
• Lambert 93 (EPSG:2154) — used in France
• Client-provided local systems
• Reprojection to any other requested system

Deliverables Compatible with GIS and AI

Annotated or processed data can be delivered ready to use in:

• QGIS, ArcGIS, PostGIS
• Geospatial AI platforms (DeepGIS, TorchGeo, RasterVision…)
• Client internal workflows

In summary, Infoscribe supports nearly all standard geospatial formats as well as the main coordinate systems used in mapping, LiDAR, remote sensing, and GIS projects.

Yes, Infoscribe can fully ensure the compatibility of essential metadata, such as projection information, capture dates, sensor parameters, or descriptive elements necessary for advanced geospatial processing.

The company places particular emphasis on the quality and consistency of metadata, as these directly affect the accuracy of GIS analyses and the performance of geospatial deep learning models. When handling data, Infoscribe systematically verifies the presence, validity, and consistency of metadata, including the coordinate system used, optical or LiDAR sensor characteristics, spatial resolutions, and temporal attributes essential for change detection or multisource analysis.

If needed, our teams can enrich, correct, or restructure metadata to meet the standards required by tools such as QGIS, ArcGIS, or PostGIS, as well as formats needed for training specialized AI models (cloud masking, land cover classification, building segmentation, etc.).

Infoscribe can also perform data reprojection, harmonize datasets from different sensors, or reconstruct a coherent metadata structure to facilitate automatic ingestion into client pipelines. This technical expertise ensures that delivered data is not only fully usable but also optimized for operational, cartographic, or AI purposes.

Through this rigorous approach, Infoscribe guarantees seamless continuity between the geospatial source and the final analytical environment, whether it is a professional GIS or a geospatial deep learning model.

Infoscribe manages the fusion of data from multiple sources by first harmonizing their metadata, formats, and coordinate systems to ensure full compatibility. Satellite imagery, drone data, LiDAR point clouds, or GIS layers are spatially and temporally aligned to ensure perfect consistency across sources. The company then applies preprocessing steps such as reprojection, coregistration, radiometric correction, or orthorectification so that each dataset can be combined without distortion or loss of accuracy.

Once this common foundation is established, Infoscribe uses specialized workflows to overlay, cross-reference, and structure information from different sensors. This may include the extraction of geographic features, object segmentation, land cover classification, or the integration of 3D data with 2D imagery. The fused data is then validated through quality controls to ensure that source correspondences are correct, any misalignments are corrected, and the results meet client requirements.

Finally, Infoscribe delivers a coherent dataset ready for use in GIS or integration into a geospatial AI pipeline. This methodology ensures that multi-source data fusion produces reliable, consistent, and actionable information suitable for advanced analyses, predictive modeling, or operational applications.